3 repositorios
Awesome GitHub RepositoriesMulti-Criteria Dataset Filtering
Filtering datasets using multiple combined attributes to refine results.
Distinct from Dataset Filters: The candidates are either too specific to package managers or map visualizations, or focus on data attribution/caching rather than UI filtering logic.
Explore 3 awesome GitHub repositories matching web development · Multi-Criteria Dataset Filtering. Refine with filters or upvote what's useful.
Awesome Multi-Criteria Dataset Filtering GitHub Repositories
Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
- mui/mui-x
mui/mui-x
5,791Ver en GitHubMUI X is a collection of advanced React UI components for building data-rich applications, including a data grid, charting library, date and time pickers, scheduler, and tree view. The library is built with accessibility as a core principle, ensuring all components meet WCAG and WAI-ARIA standards for keyboard navigation and screen reader announcements. The components are designed for extensibility and performance. The data grid offers comprehensive data management with sorting, filtering, pagination, column pinning, row grouping, inline editing, and Excel export. The charting library support
Applies complex filter conditions across columns to narrow down displayed rows in the data grid.
TypeScriptchartsdata-griddatatable - midudev/jscamp
midudev/jscamp
3,811Ver en GitHubjscamp is a full-stack web development and education project focused on mastering JavaScript, TypeScript, and AI integration. It provides a structured curriculum and interactive exercises covering language fundamentals, frontend engineering, and backend API development. The project distinguishes itself through the implementation of autonomous AI agents capable of complex task automation, such as modifying files, managing servers, and executing API calls. It includes advanced AI development tools for conversational querying, real-time code suggestions, and automated repository analysis to gene
Implements logic to restrict datasets based on multiple matching attributes for refined search results.
JavaScriptbootcamp - fasiondog/hikyuu
fasiondog/hikyuu
2,999Ver en GitHubHikyuu is a quantitative trading framework designed for developing, backtesting, and executing systematic trading strategies. It functions as a high-speed system that combines a financial time-series library, a multi-factor analysis tool, and a quantitative backtesting engine to support comprehensive trading research. The framework is distinguished by its high-speed computing core, which utilizes multi-threaded execution to process large volumes of market data for technical indicator generation. It supports a modular strategy composition model where signal, risk, and fund management component
Selects stocks based on specific criteria, blocks, or multi-factor rankings using cross-sectional scoring.
C++algorithms-tradingbacktestingcpp
